Your browser doesn't support javascript.
loading
Mostrar: 20 | 50 | 100
Resultados 1 - 2 de 2
Filtrar
Mais filtros

Base de dados
Ano de publicação
Tipo de documento
Assunto da revista
País de afiliação
Intervalo de ano de publicação
1.
FEMS Microbiol Lett ; 273(2): 224-8, 2007 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-17559407

RESUMO

Metagenomic analyses suggest that the rank-abundance curve for marine phage communities follows a power law distribution. A new type of power law dependence based on a simple model in which a modified version of Lotka-Volterra predator-prey dynamics is sampled uniformly in time is presented. Biologically, the model embodies a kill the winner hypothesis and a neutral evolution hypothesis. The model can match observed power law distributions and uses very few parameters that are readily identifiable and characterize phage ecosystems. The model makes new untested predictions: (1) it is unlikely that the most abundant phage genotype will be the same at different time points and (2) the long-term decay of isolated phage populations follows a power law.


Assuntos
Bacteriófagos/crescimento & desenvolvimento , Modelos Biológicos , Microbiologia da Água , Ecossistema
2.
BMC Bioinformatics ; 6: 41, 2005 Mar 02.
Artigo em Inglês | MEDLINE | ID: mdl-15743531

RESUMO

BACKGROUND: Phages, viruses that infect prokaryotes, are the most abundant microbes in the world. A major limitation to studying these viruses is the difficulty of cultivating the appropriate prokaryotic hosts. One way around this limitation is to directly clone and sequence shotgun libraries of uncultured viral communities (i.e., metagenomic analyses). PHACCS http://phage.sdsu.edu/phaccs, Phage Communities from Contig Spectrum, is an online bioinformatic tool to assess the biodiversity of uncultured viral communities. PHACCS uses the contig spectrum from shotgun DNA sequence assemblies to mathematically model the structure of viral communities and make predictions about diversity. RESULTS: PHACCS builds models of possible community structure using a modified Lander-Waterman algorithm to predict the underlying contig spectrum. PHACCS finds the most appropriate structure model by optimizing the model parameters until the predicted contig spectrum is as close as possible to the experimental one. This model is the basis for making estimates of uncultured viral community richness, evenness, diversity index and abundance of the most abundant genotype. CONCLUSION: PHACCS analysis of four different environmental phage communities suggests that the power law is an important rank-abundance form to describe uncultured viral community structure. The estimates support the fact that the four phage communities were extremely diverse and that phage community biodiversity and structure may be correlated with that of their hosts.


Assuntos
Biologia Computacional/métodos , Mapeamento de Interação de Proteínas/métodos , Software , Vírus/metabolismo , Algoritmos , Bacteriófagos/metabolismo , Biodiversidade , Mapeamento de Sequências Contíguas , DNA/química , Vírus de DNA , Bases de Dados Genéticas , Genes Virais , Variação Genética , Genoma Viral , Genótipo , Internet , Modelos Genéticos , Modelos Estatísticos , Análise de Sequência de DNA
SELEÇÃO DE REFERÊNCIAS
DETALHE DA PESQUISA